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Llama 3.3 70b Instruct

meta-llama/llama-3.3-70b-instruct
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Llama 3.3 70b Instruct

meta-llama/llama-3.3-70b-instruct

Llama 3.3 is optimized for multilingual dialogue use cases and outperforms many of the available open source and closed chat models on common industry benchmarks.

Added Feb 27, 2025

Model weights

Context Window

131.1K

Max Output

16.4K

Input Price (Auto)

$0.100/1M

Output Price (Auto)

$0.32/1M

Cache Read (Auto)

$0.050/1M

Capabilities

Benchmarks

Performance metrics and benchmarks

Sourced from Artificial Analysis.

Intelligence Index

9.3

Better than 29% of models compared

Coding Index

11.9

Better than 13% of models compared

Reasoning

GPQA Diamond

Graduate-level scientific reasoning

49.8%

Better than 25% of models compared

HLE

Humanity's Last Exam

3.6%

Better than 7% of models compared

IFBench

Instruction-following benchmark

47.1%

Better than 55% of models compared

T²-Bench Telecom

Conversational AI agents in dual-control scenarios

26.6%

Better than 32% of models compared

AA-LCR

Long context reasoning evaluation

15.7%

Better than 24% of models compared

GDPval-AA

Economically valuable tasks

0.0%

CritPt

Research-level physics reasoning

0.0%

Coding

SciCode

Python programming for scientific computing

26.0%

Better than 30% of models compared

Terminal-Bench Hard

Agentic coding and terminal use

3.0%

Better than 23% of models compared

LiveCodeBench

Contamination-free coding benchmark

28.8%

Better than 32% of models compared

Math

AIME 2025

American Invitational Mathematics Examination 2025

7.7%

Better than 12% of models compared

AIME

American Invitational Mathematics Examination

30.0%

Better than 57% of models compared

Math-500

Diverse mathematical problem solving benchmark

77.3%

Better than 42% of models compared

Knowledge

MMLU-Pro

Professional and academic subject knowledge

71.3%

Better than 39% of models compared

AA-Omniscience Accuracy

Proportion of correctly answered questions

19.0%

AA-Omniscience Hallucination Rate

Rate of incorrect answers among non-correct responses

90.2%

Last updated Aug 16, 2026

Artificial Analysis

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